eQTL mapping in response to osteoarthritis induction in differentiated skeletal cell types

分化骨骼细胞类型中骨关节炎诱导反应的 eQTL 作图

• 批准号: 10152350
• 负责人: Genevieve Housman
• 金额: $ 7.25万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10152350
• 关键词: Accounting; Affect; Age; Arthritis; Attention; Biomechanics; Candidate Disease Gene; Cell Culture Techniques; Cells; Chondrocytes; Complex; Data; Degenerative polyarthritis; Disease; Disease Progression; Environmental Risk Factor; Etiology; European; Gene Expression; Gene Expression Profile; Genetic; Genome; Genotype; Health; Human; Individual; Joints; Lead; Mechanical Stress; Mediating; Modeling; Molecular; Osteoblasts; Pathogenesis; Periodicity; Phenotype; Population; Productivity; Public Health; Publishing; Quantitative Trait Loci; Regulator Genes; Research; Resolution; Risk; Sampling; Skeletal system; Source; Stress; Testing; Treatment Cost; Variant; Woman; Work; age effect; arthropathies; biological adaptation to stress; bone; cartilage cell; cartilage degradation; cell type; cohort; comparative; differentiation protocol; disability; disease phenotype; droplet sequencing; experience; gene environment interaction; genetic association; genome wide association study; hutterite; in vitro Model; individual variation; induced pluripotent stem cell; insight; inter-individual variation; men; motor impairment; osteoblast differentiation; response; side effect; single-cell RNA sequencing; skeletal; trait; transcriptome sequencing

Project Summary/Abstract Osteoarthritis (OA) is a joint disease characterized by the degradation of cartilage and underlying bone, and it is a major source of disability1 and financial burden2,3 worldwide. While progress has been made towards recognizing OA as a complex disorder4, the mechanisms that initiate and mediate the onset of OA pathogenesis are still unclear. Genetic markers5–19 and environmental influences such as biomechanical stress20–24 have been associated with joint health, and alterations in gene expression regulation25–36 may connect and reinforce these factors’ involvement in disease progression. To better characterize the degree to which gene expression patterns in skeletal cells relate to underlying genotypes and are altered in response to biomechanical forces, we will use a large panel of differentiated human chondrocytes and osteoblasts to identify inter-individual variation in gene expression responses to mechanical stress treatments. Specifically, in Aim 1, I will differentiate chondrocytes and osteoblasts from 70 human induced pluripotent stem cells (iPSCs) and characterize gene expression in these cell types using bulk and single-cell data. The proposed study will include a previously characterized panel of iPSCs from 70 fully sequenced Hutterite individuals37,38 and will use established chondrocyte and osteoblast differentiation protocols39. Drop-seq single-cell RNA-seq data will be collected in addition to bulk RNA-seq data so that I can characterize inter-individual variability in gene expression and account for variation in cell composition across samples. In Aim 2, I will treat differentiated chondrocytes and osteoblasts with biomechanical stress to identify response expression quantitative trait loci (eQTLs). To do this, I will subject terminally differentiated chondrocytes and osteoblasts to established cyclic tensile strain treatments that serve as an in vitro model of OA40–43. Response eQTLs will be determined using bulk RNA-seq data, and the degree to which biomechanical stress response is robust will be estimated using single-cell data. Finally, in Aim 3, I will integrate biomechanical stress response eQTLs with genome-wide association study (GWAS) data to identify variants associated with OA risk and the underlying molecular mechanisms. Several genetic associations with OA have been identified in individuals of primarily European decent6,8–19. Since the panel of cells in the proposed study consists of a homogeneous population that represents much of European genetic diversity44, it is an ideal comparative sample set. I will determine the disease- relevance of our response eQTLs by testing for enrichment of OA GWAS hits and evaluating colocalization. Overall, this research will identify and characterize inter-individual gene expression responses in a population- scale cell culture model of OA. Further, this work will produce the largest panel of human iPSC-derived chondrocytes and osteoblasts and is expected to yield substantial insight into the gene-by-environment interactions that contribute to disease phenotypes in the skeletal system.

项目总结/摘要 骨关节炎（OA）是一种以软骨和底层骨骼退化为特征的关节疾病，它是 是全世界残疾1和财政负担2，3的主要来源。虽然在实现 认识到OA是一种复杂的疾病4，启动和介导OA发作的机制 发病机制尚不清楚。遗传标记5 -19和环境影响，如生物力学 压力20 -24与关节健康有关，基因表达调节的改变25 -36可能与 并强化这些因素对疾病进展的参与。为了更好地描述基因 骨骼细胞中的表达模式与潜在的基因型有关， 我们将使用大量分化的人类软骨细胞和成骨细胞来识别个体间的 对机械应力处理的基因表达响应的变化。具体来说，在目标1中，我将区分 软骨细胞和成骨细胞从70人诱导多能干细胞（iPSC），并表征 基因表达在这些细胞类型使用批量和单细胞数据。拟议的研究将包括 先前表征的来自70个完全测序的Hutterite个体的iPSC组37，38，并将使用已建立的 软骨细胞和成骨细胞分化方案39. Drop-seq单细胞RNA-seq数据将在 除了批量RNA-seq数据，我可以表征基因表达的个体间变异性， 解释了样品间细胞组成的变化。在目标2中，我将处理分化的软骨细胞， 成骨细胞与生物力学应力，以确定响应表达数量性状基因座（eQTL）。到 这样，我将使终末分化的软骨细胞和成骨细胞经受既定的循环拉伸应变 作为OA 40 -43体外模型的治疗。响应eQTL将使用批量RNA-seq 数据，以及生物力学应力响应稳健的程度将使用单细胞数据进行估计。 最后，在目标3中，我将整合生物力学应激反应eQTL与全基因组关联 研究（GWAS）数据，以确定与OA风险相关的变异和潜在的分子 机制等已经在主要是欧洲人的个体中确定了与OA的几种遗传关联。 decent6，8-19.由于拟议研究中的一组细胞由同质群体组成， 大部分欧洲遗传多样性44，这是一个理想的比较样本集。我来决定疾病- 通过测试OA GWAS命中物的富集和评估共定位来确定我们的响应eQTL的相关性。 总的来说，这项研究将确定和表征人群中个体间的基因表达反应- OA的细胞培养模型。此外，这项工作将产生最大的人类iPSC衍生的面板。 软骨细胞和成骨细胞，并有望产生大量的洞察基因的环境 这些相互作用导致骨骼系统中的疾病表型。